title: Analysis of nonlinear gene expression progression reveals extensive pathway and age-specific transitions in aging human brains.
abstract: Several recent gene expression studies identified hundreds of genes that are correlated with age in brain and other tissues in human. However, these studies used linear models of age correlation, which are not well equipped to model abrupt changes associated with particular ages. We developed a computational algorithm for age estimation in which the expression of each gene is treated as a dichotomized biomarker for whether the subject is older or younger than a particular age. In addition, for each age-informative gene our algorithm identifies the age threshold with the most drastic change in expression level, which allows us to associate genes with particular age periods. Analysis of human aging brain expression datasets from three frontal cortex regions showed that different pathways undergo transitions at different ages, and the distribution of pathways and age thresholds varies across brain regions. Our study reveals age-correlated expression changes at particular age points and allows one to estimate the age of an individual with better accuracy than previously published methods.
authors.affiliation: Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America ; Penn Center for Bioinformatics, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
authors.forename: Kajia
authors.initials: K
authors.lastname: Cao
authors.forename: Paul
authors.initials: P
authors.lastname: Ryvkin
authors.forename: Yih-Chii
authors.initials: YC
authors.lastname: Hwang
authors.forename: F Brad
authors.initials: FB
authors.lastname: Johnson
authors.forename: Li-San
authors.initials: LS
authors.lastname: Wang
mesh_terms: D000328:Adult; D000368:Aged; D000375:Aging / Q000235:genetics* / Q000378:metabolism; D001499:Bayes Theorem; D001921:Brain / Q000378:metabolism*; D019295:Computational Biology / Q000379:methods*; D015536:Down-Regulation / Q000502:physiology; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D017711:Nonlinear Dynamics; D060066:Protein Interaction Maps / Q000235:genetics; D059467:Transcriptome / Q000502:physiology*